This is a video tutorial that will try to teach you how to use R for spatial statistics and interpolation.

For my work I often use R, particularly for geostatstical interpolation. Despite R being a very powerful statistical language, which has became a benchmark for spatial statistics, it is also a relatively difficult language to learn with one of the steepest learning curve among programming languages.

For this reason I though about sharing my experience to hopefully ease the learning process. I prepared this video tutorial because I think that the easy way of learning R is by following examples.

The tutorial is structured as follow: the first two lessons are about the basics of R, how to handle R objects, plotting and saving your work. This part is intended for beginners who want to learn the language. Starting from the third lesson I will show examples on how to handle and plotting spatial data and rasters, and in the last two lessons I will show you how to perform ordinary and universal kriging in R.

In this tutorial I will show you some examples that will hopefully help you learning R in a quicker and easier way. However, this course is not a complete R course, because R has lots and lots of different functions for every branch of science. For this reason at the beginning of the course and at the end of each lesson, if appropriate, I will give you some references if you want to deepen your knowledge.

If you have any suggestion on how to improve the course or if you have any feedback that you want to share, please send an e-mail to:

Below you can find the structure of the course, and links to the zip files with the script and the datasets that I will use for each lesson.

- Introduction

Video - Presentation - Tutorial 1 - Basics of R

Video - Presentation - Tutorial 2 - Plotting

Video - Presentation - Tutorial 3 - Spatial Data

Video - Presentation - Tutorial 4 - Ordinary Kriging

Video - Presentation - Tutorial 5 - Universal Kriging

Video - Presentation - Tutorial 6 - CoKriging

Video - Presentation